{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Day05 基础构图元素：坐标轴篇（中）\n",
    "\n",
    "　　接着上一个日程的内容，我们继续来学习`matplotlib`中关于**坐标轴**的更多知识："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:31.560415Z",
     "iopub.status.busy": "2020-10-17T14:59:31.560415Z",
     "iopub.status.idle": "2020-10-17T14:59:31.779794Z",
     "shell.execute_reply": "2020-10-17T14:59:31.779794Z",
     "shell.execute_reply.started": "2020-10-17T14:59:31.560415Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matplotlib版本： 3.3.2\n"
     ]
    }
   ],
   "source": [
    "import matplotlib;print('matplotlib版本：', matplotlib.__version__)\n",
    "import matplotlib.pyplot as plt # 从matplotlib中导入我们最经常使用的pyplot子模块\n",
    "import pandas as pd # 用于处理外部数据集\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] # 设定默认字体为SimHei以解决中文显示乱码问题\n",
    "plt.rcParams['axes.unicode_minus'] = False # 解决图像负号'-'不正常显示的问题"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:31.780792Z",
     "iopub.status.busy": "2020-10-17T14:59:31.780792Z",
     "iopub.status.idle": "2020-10-17T14:59:31.807754Z",
     "shell.execute_reply": "2020-10-17T14:59:31.807754Z",
     "shell.execute_reply.started": "2020-10-17T14:59:31.780792Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>species</th>\n",
       "      <th>island</th>\n",
       "      <th>bill_length_mm</th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "      <th>body_mass_g</th>\n",
       "      <th>sex</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.1</td>\n",
       "      <td>18.7</td>\n",
       "      <td>181.0</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>186.0</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>40.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>36.7</td>\n",
       "      <td>19.3</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3450.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.3</td>\n",
       "      <td>20.6</td>\n",
       "      <td>190.0</td>\n",
       "      <td>3650.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
       "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
       "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
       "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
       "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
       "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
       "\n",
       "   body_mass_g     sex  year  \n",
       "0       3750.0    male  2007  \n",
       "1       3800.0  female  2007  \n",
       "2       3250.0  female  2007  \n",
       "4       3450.0  female  2007  \n",
       "5       3650.0    male  2007  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 读入数据并删除含有缺失值的行\n",
    "data = pd.read_csv('penguins.csv').dropna()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **坐标轴整体调整**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　利用`axis('off')`可以直接关闭x轴与y轴："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:31.810712Z",
     "iopub.status.busy": "2020-10-17T14:59:31.810712Z",
     "iopub.status.idle": "2020-10-17T14:59:31.902466Z",
     "shell.execute_reply": "2020-10-17T14:59:31.902466Z",
     "shell.execute_reply.started": "2020-10-17T14:59:31.810712Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "ax.axis('off'); # 关闭坐标轴"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　利用`axis('equal')`可以让x轴和y轴显示范围保持一致，譬如下面的例子中，设置`axis('equal')`后x轴看起来被压缩了很多："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:31.904459Z",
     "iopub.status.busy": "2020-10-17T14:59:31.904459Z",
     "iopub.status.idle": "2020-10-17T14:59:32.038103Z",
     "shell.execute_reply": "2020-10-17T14:59:32.038103Z",
     "shell.execute_reply.started": "2020-10-17T14:59:31.904459Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "ax.axis('equal'); # 强制x轴与y轴显示范围保持一致"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　利用`xaxis.tick_top()`可以强制x轴出现在顶部："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:32.039146Z",
     "iopub.status.busy": "2020-10-17T14:59:32.039146Z",
     "iopub.status.idle": "2020-10-17T14:59:32.211640Z",
     "shell.execute_reply": "2020-10-17T14:59:32.210643Z",
     "shell.execute_reply.started": "2020-10-17T14:59:32.039146Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "ax.xaxis.tick_top();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　同理也可以设置y轴的方位："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:32.213634Z",
     "iopub.status.busy": "2020-10-17T14:59:32.212637Z",
     "iopub.status.idle": "2020-10-17T14:59:32.377200Z",
     "shell.execute_reply": "2020-10-17T14:59:32.376199Z",
     "shell.execute_reply.started": "2020-10-17T14:59:32.212637Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "ax.yaxis.tick_right();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **自定义坐标轴显示刻度位置及对应刻度标签**\n",
    "\n",
    "　　利用`set_{x或y}ticks()`，可以自定义对应的坐标轴显示的刻度在哪些位置，而`set_{x或y}ticklabels()`可以配合`set_{x或y}ticks()`设置一一对应的文字标签："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:32.379191Z",
     "iopub.status.busy": "2020-10-17T14:59:32.379191Z",
     "iopub.status.idle": "2020-10-17T14:59:32.509841Z",
     "shell.execute_reply": "2020-10-17T14:59:32.509841Z",
     "shell.execute_reply.started": "2020-10-17T14:59:32.379191Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "\n",
    "ax.scatter(data['bill_length_mm'], data['body_mass_g'])\n",
    "\n",
    "ax.set_xticks([10, 20, 30, 40, 50, 60, 70, 75]); # 自定义刻度位置\n",
    "ax.set_xticklabels(list('ABCDEFGH'), \n",
    "                   fontdict={\n",
    "                       'fontsize': 20, # 控制字体大小\n",
    "                       'color': 'red', # 控制文字颜色\n",
    "                       'rotation': 45 # 控制文字旋转角度\n",
    "                   });"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 课后测验：\n",
    "\n",
    "　　相信通过上面的内容，你已经对如何更好的控制坐标轴及刻度信息有了新的认识，下面请你结合今天所学的内容，基于下面这段原始朴素的绘图代码："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-10-17T14:59:32.511836Z",
     "iopub.status.busy": "2020-10-17T14:59:32.511836Z",
     "iopub.status.idle": "2020-10-17T14:59:32.623537Z",
     "shell.execute_reply": "2020-10-17T14:59:32.623537Z",
     "shell.execute_reply.started": "2020-10-17T14:59:32.511836Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1uK+xhs8m+coY42JVbWiqxV09f5JU1avzu+3+/qOf6FBekeTc5Y9/keRPNzjL0hpv/yT5dBrt/9dxbzbUoZaHSpL8JMlrL3+8m/VcC2Xd3pnkE1V1NskbquprG55nksvPmJ5K8sgYo9v2fykvH1d9ZRp+HzTf/knz/f+yjXWo5e9xV9UfJvl6kjuSnEjygTHGuYNvdXxV1dkxxn2bnmOKqvqrJH+f5D8vf+rxMcY/bXCkhVXVR5L88Rjj0ar6myTPjzH+cdNzTdF5+1+t4/6fbLZDLcMNh1FVf5TkB0n+Pcl7krxpjPE/m50KFifcbKWqui3JA0m+P8Zo+VsNbC/hBmim3Q9lALadcAM0I9wAzQg3QDPCDdDM/wJDxkQdrE4M8gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "x = np.linspace(-2*np.pi, 2*np.pi, 25)\n",
    "y = np.sin(x)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "\n",
    "ax.axis('equal');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "　　按照你对今天内容的理解，尽可能地还原出下面这张图（提示：π）：\n",
    "  \n",
    "<center><img src='imgs/demo.png' width=500></img></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 请在今天对应的帖子下回复你的文字代码及绘图结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "x = np.linspace(-2*np.pi, 2*np.pi, 25)\n",
    "y = np.sin(x)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y)\n",
    "ax.xaxis.tick_top();\n",
    "ax.axis('equal')\n",
    "ax.set_yticks(range(-8,9,2)) # 自定义刻度位置\n",
    "ax.set_xticks([-2*np.pi, -1*np.pi,0,np.pi,2*np.pi]);\n",
    "ax.set_xticklabels(['-2π','-π','0','π','2π'], \n",
    "                   fontdict={\n",
    "                       'fontsize': 20, \n",
    "                       'color': 'black' \n",
    "                   });"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
